## COMPUTE ANALYSES AND GRAPHICS
categorical_results <- merged_lm_responses_to_predictors(scores_grit_esfuer_preoc, categorical_info, threshold_significance = 0.05, categorical_flag = FALSE,
side = 1, cex = 0.5, pch = 1.1, alpha = 1/3, size = 1.1)
## $fG
## $fG$escuela
## xcepac xprimcongreso xsecaugusto
## 8.453539e-16 6.966841e-03 1.962082e-07
##
## $fG$grado
## x1b x2a x3a x3b x6 x8
## 0.002125176 0.002636762 0.001098538 0.004825131 0.034494787 0.037487880
## x9
## 0.046386617
##
## $fG$ciudad
## xcdmx xguadalajara
## 6.772918e-11 9.875281e-36
##
## $fG$capacidad
## [1] 2.005137e-17
##
##
## $Tenaci
## $Tenaci$escuela
## xprimcongreso
## 0.006709368
##
## $Tenaci$grado
## x6a x6c
## 0.009994055 0.003121953
##
## $Tenaci$ciudad
## xcdmx
## 0.001419448
##
## $Tenaci$nacionalidad
## xmexicano
## 0.006650907
##
## $Tenaci$capacidad
## [1] 0.04793674
##
##
## $Esfuer
## $Esfuer$escuela
## xprimcongreso
## 0.04431305
##
## $Esfuer$grado
## x1d x2b x2c x3a x6a x6c
## 0.044021673 0.002543359 0.001648638 0.027042924 0.012576949 0.030856235
##
## $Esfuer$ciudad
## xcdmx xguadalajara
## 0.003100297 0.008215657
##
## $Esfuer$nacionalidad
## xmexicano
## 0.003205683
##
##
## $Preocu
## $Preocu$escuela
## xcepac
## 0.004002426
##
## $Preocu$grado
## x2c
## 0.003962269
##
## $Preocu$ciudad
## xguadalajara
## 2.899829e-05
##
## $Preocu$nacionalidad
## xmexicano
## 0.0002189558
##
##
## [1] "fG escuela"
## [1] "fG grado"
## [1] "fG ciudad"
## [1] "fG capacidad"
## [1] "Tenaci escuela"
## [1] "Tenaci grado"
## [1] "Tenaci ciudad"
## [1] "Tenaci nacionalidad"
## [1] "Tenaci capacidad"
## [1] "Esfuer escuela"
## [1] "Esfuer grado"
## [1] "Esfuer ciudad"
## [1] "Esfuer nacionalidad"
## [1] "Preocu escuela"
## [1] "Preocu grado"
## [1] "Preocu ciudad"
## [1] "Preocu nacionalidad"
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF fG IN escuela GROUPS ==="
## # A tibble: 10 x 4
## escuela mean sd num
## <fct> <dbl> <dbl> <int>
## 1 andes 101. 10.9 63
## 2 bicentenario 100. 11.4 67
## 3 cepac 116. 12.1 101
## 4 coltec 98 11.2 49
## 5 diosa 98.9 11.3 265
## 6 esperanza 96.8 11.2 19
## 7 pidahi 104. 9.67 25
## 8 primcongreso 95.9 12.9 81
## 9 secaugusto 92.6 11.9 247
## 10 villavicencio 99.3 10.8 285
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF fG IN grado GROUPS ==="
## # A tibble: 20 x 4
## grado mean sd num
## <fct> <dbl> <dbl> <int>
## 1 1a 94.3 13.2 32
## 2 1b 104. 19.9 35
## 3 1c 92.0 15.0 26
## 4 1d 99.3 16.4 31
## 5 2a 103. 14.0 52
## 6 2b 100. 14.2 34
## 7 2c 100. 14.7 38
## 8 2d 100. 12.4 28
## 9 3a 104. 14.2 36
## 10 3b 104. 21.0 29
## 11 3c 88.3 8.54 15
## 12 3d 95.6 13.6 17
## 13 6 99.4 11.1 252
## 14 6a 94.0 11.4 21
## 15 6b 97.2 7.47 16
## 16 6c 95.5 18.2 19
## 17 6d 96.9 12.7 25
## 18 7 98.7 11.6 195
## 19 8 99.4 10.9 172
## 20 9 99.3 10.7 129
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF fG IN ciudad GROUPS ==="
## # A tibble: 6 x 4
## ciudad mean sd num
## <fct> <dbl> <dbl> <int>
## 1 bogota 99.6 11.0 443
## 2 cajica 95.1 6.88 15
## 3 cdmx 94.2 12.4 353
## 4 chia 98.9 11.5 242
## 5 funza 98.3 11.1 48
## 6 guadalajara 116. 12.1 101
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF fG IN capacidad GROUPS ==="
## # A tibble: 2 x 4
## capacidad mean sd num
## <fct> <dbl> <dbl> <int>
## 1 alta 102. 12.8 560
## 2 tipica 96.3 12.1 642
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Tenaci IN escuela GROUPS ==="
## # A tibble: 10 x 4
## escuela mean sd num
## <fct> <dbl> <dbl> <int>
## 1 andes 3.20 0.642 63
## 2 bicentenario 3.28 0.603 67
## 3 cepac 3.24 0.524 101
## 4 coltec 3.13 0.686 49
## 5 diosa 3.22 0.580 265
## 6 esperanza 3.08 0.605 19
## 7 pidahi 3.26 0.612 25
## 8 primcongreso 2.91 0.625 81
## 9 secaugusto 3.11 0.650 247
## 10 villavicencio 3.21 0.642 285
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Tenaci IN grado GROUPS ==="
## # A tibble: 20 x 4
## grado mean sd num
## <fct> <dbl> <dbl> <int>
## 1 1a 3.18 0.602 32
## 2 1b 3.17 0.653 35
## 3 1c 3.33 0.779 26
## 4 1d 2.92 0.738 31
## 5 2a 3.31 0.586 52
## 6 2b 2.95 0.552 34
## 7 2c 3.10 0.560 38
## 8 2d 3.11 0.685 28
## 9 3a 3.10 0.481 36
## 10 3b 3.38 0.559 29
## 11 3c 3.12 0.457 15
## 12 3d 3.12 0.609 17
## 13 6 3.22 0.634 252
## 14 6a 2.74 0.578 21
## 15 6b 2.97 0.470 16
## 16 6c 2.66 0.714 19
## 17 6d 3.22 0.567 25
## 18 7 3.17 0.605 195
## 19 8 3.23 0.637 172
## 20 9 3.23 0.585 129
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Tenaci IN ciudad GROUPS ==="
## # A tibble: 6 x 4
## ciudad mean sd num
## <fct> <dbl> <dbl> <int>
## 1 bogota 3.22 0.635 443
## 2 cajica 3.04 0.453 15
## 3 cdmx 3.08 0.647 353
## 4 chia 3.22 0.582 242
## 5 funza 3.14 0.690 48
## 6 guadalajara 3.24 0.524 101
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Tenaci IN nacionalidad GROUPS ==="
## # A tibble: 3 x 4
## nacionalidad mean sd num
## <fct> <dbl> <dbl> <int>
## 1 colombiano 3.21 0.624 703
## 2 mexicano 3.11 0.625 454
## 3 venezolano 3.16 0.518 45
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Tenaci IN capacidad GROUPS ==="
## # A tibble: 2 x 4
## capacidad mean sd num
## <fct> <dbl> <dbl> <int>
## 1 alta 3.21 0.618 560
## 2 tipica 3.14 0.625 642
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Esfuer IN escuela GROUPS ==="
## # A tibble: 10 x 4
## escuela mean sd num
## <fct> <dbl> <dbl> <int>
## 1 andes 48.1 9.87 63
## 2 bicentenario 48.4 9.90 67
## 3 cepac 45.3 10.9 101
## 4 coltec 46.1 8.37 49
## 5 diosa 47.0 8.99 265
## 6 esperanza 48.6 11.0 19
## 7 pidahi 46.1 10.7 25
## 8 primcongreso 45.1 8.27 81
## 9 secaugusto 46.4 7.86 247
## 10 villavicencio 47.7 8.27 285
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Esfuer IN grado GROUPS ==="
## # A tibble: 20 x 4
## grado mean sd num
## <fct> <dbl> <dbl> <int>
## 1 1a 49.6 6.61 32
## 2 1b 47.4 7.77 35
## 3 1c 46.0 10.6 26
## 4 1d 45.1 8.46 31
## 5 2a 47.3 9.58 52
## 6 2b 43 10.7 34
## 7 2c 42.9 10.0 38
## 8 2d 45.6 8.02 28
## 9 3a 44.8 9.42 36
## 10 3b 47.9 8.09 29
## 11 3c 46.5 5.37 15
## 12 3d 48 7.32 17
## 13 6 47.4 9.27 252
## 14 6a 43.4 6.41 21
## 15 6b 46.4 7.23 16
## 16 6c 44.1 10.6 19
## 17 6d 46.4 8.39 25
## 18 7 48.2 8.75 195
## 19 8 46.7 8.87 172
## 20 9 47.7 8.37 129
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Esfuer IN ciudad GROUPS ==="
## # A tibble: 6 x 4
## ciudad mean sd num
## <fct> <dbl> <dbl> <int>
## 1 bogota 47.9 8.86 443
## 2 cajica 48.5 7.94 15
## 3 cdmx 46.1 8.18 353
## 4 chia 46.9 9.08 242
## 5 funza 46.1 8.45 48
## 6 guadalajara 45.3 10.9 101
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Esfuer IN nacionalidad GROUPS ==="
## # A tibble: 3 x 4
## nacionalidad mean sd num
## <fct> <dbl> <dbl> <int>
## 1 colombiano 47.5 9.01 703
## 2 mexicano 45.9 8.85 454
## 3 venezolano 47.9 6.74 45
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Preocu IN escuela GROUPS ==="
## # A tibble: 10 x 4
## escuela mean sd num
## <fct> <dbl> <dbl> <int>
## 1 andes 63.2 17.6 63
## 2 bicentenario 60.9 15.3 67
## 3 cepac 55.6 19.8 101
## 4 coltec 66.2 14.2 49
## 5 diosa 64.8 17.0 265
## 6 esperanza 62.4 17.4 19
## 7 pidahi 59.4 19.0 25
## 8 primcongreso 60.5 16.9 81
## 9 secaugusto 62.6 14.5 247
## 10 villavicencio 64.0 16.0 285
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Preocu IN grado GROUPS ==="
## # A tibble: 20 x 4
## grado mean sd num
## <fct> <dbl> <dbl> <int>
## 1 1a 64.5 16.8 32
## 2 1b 60.1 17.7 35
## 3 1c 63.2 16.1 26
## 4 1d 59.2 13.2 31
## 5 2a 60.6 18.0 52
## 6 2b 57.4 16.5 34
## 7 2c 53.1 15.5 38
## 8 2d 61.5 17.2 28
## 9 3a 61.4 18.3 36
## 10 3b 63.1 17.4 29
## 11 3c 64.5 13.3 15
## 12 3d 63.4 13.8 17
## 13 6 64.3 17.0 252
## 14 6a 57.9 13.3 21
## 15 6b 58.5 12.0 16
## 16 6c 60.9 20.0 19
## 17 6d 63.8 19.9 25
## 18 7 64.5 16.9 195
## 19 8 62.7 14.3 172
## 20 9 64.5 16.9 129
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Preocu IN ciudad GROUPS ==="
## # A tibble: 6 x 4
## ciudad mean sd num
## <fct> <dbl> <dbl> <int>
## 1 bogota 63.2 16.3 443
## 2 cajica 66.9 17.1 15
## 3 cdmx 61.9 15.4 353
## 4 chia 64.9 16.8 242
## 5 funza 66.2 14.4 48
## 6 guadalajara 55.6 19.8 101
## [1] "=== GROUP DIFFERENCES GRAPH ==="
## [1] "=== DESCRIPTIVE STATS OF Preocu IN nacionalidad GROUPS ==="
## # A tibble: 3 x 4
## nacionalidad mean sd num
## <fct> <dbl> <dbl> <int>
## 1 colombiano 64.2 16.3 703
## 2 mexicano 60.5 16.7 454
## 3 venezolano 61.5 17.8 45
##
## Attaching package: 'gridExtra'
## The following object is masked from 'package:dplyr':
##
## combine
# SHOW RESULTS
categorical_results
## $fG
## $fG$escuela
## xcepac xprimcongreso xsecaugusto
## 8.453539e-16 6.966841e-03 1.962082e-07
##
## $fG$grado
## x1b x2a x3a x3b x6 x8
## 0.002125176 0.002636762 0.001098538 0.004825131 0.034494787 0.037487880
## x9
## 0.046386617
##
## $fG$ciudad
## xcdmx xguadalajara
## 6.772918e-11 9.875281e-36
##
## $fG$capacidad
## [1] 2.005137e-17
##
##
## $Tenaci
## $Tenaci$escuela
## xprimcongreso
## 0.006709368
##
## $Tenaci$grado
## x6a x6c
## 0.009994055 0.003121953
##
## $Tenaci$ciudad
## xcdmx
## 0.001419448
##
## $Tenaci$nacionalidad
## xmexicano
## 0.006650907
##
## $Tenaci$capacidad
## [1] 0.04793674
##
##
## $Esfuer
## $Esfuer$escuela
## xprimcongreso
## 0.04431305
##
## $Esfuer$grado
## x1d x2b x2c x3a x6a x6c
## 0.044021673 0.002543359 0.001648638 0.027042924 0.012576949 0.030856235
##
## $Esfuer$ciudad
## xcdmx xguadalajara
## 0.003100297 0.008215657
##
## $Esfuer$nacionalidad
## xmexicano
## 0.003205683
##
##
## $Preocu
## $Preocu$escuela
## xcepac
## 0.004002426
##
## $Preocu$grado
## x2c
## 0.003962269
##
## $Preocu$ciudad
## xguadalajara
## 2.899829e-05
##
## $Preocu$nacionalidad
## xmexicano
## 0.0002189558
Analysis of association among the following variables:
Correlation Analisis.
scatterplot_significant_correlations(cormatrixrows, cormatrixrcols, sign=0.05)
## [1] "Tenaci Esfuer _ r = 0.31817045 _ pval = 0"
## [1] "fG Preocu _ r = -0.0859733 _ pval = 0.003"
## [1] "Tenaci Preocu _ r = 0.18849035 _ pval = 0"
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## `geom_smooth()` using formula = 'y ~ x'
## [[1]]
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## [[2]]
## [[2]][[1]]
## `geom_smooth()` using formula = 'y ~ x'
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## [[2]][[2]]
## `geom_smooth()` using formula = 'y ~ x'
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## [[2]][[3]]
## `geom_smooth()` using formula = 'y ~ x'